About

Hannah Lui Park, Ph.D., is the Principal Investigator and an Associate Professor In Residence at the University of California, Irvine. She serves as the Vice-Chair for Wellness in the Department of Pathology & Laboratory Medicine and is also affiliated with the Department of Epidemiology & Biostatistics at the UC Irvine School of Medicine. Dr. Park leads the Park Lab, which is involved in various research projects and includes a diverse team of interns, students, and graduate researchers from multiple disciplines and institutions. Her professional role encompasses leadership in both academic and research settings within the fields of pathology, laboratory medicine, epidemiology, and biostatistics.

Research topics

• Biology
• Internal medicine
• Medicine
• Environmental health
• Genetics
• Oncology
• Pathology
• Biotechnology
• Bioinformatics
• Toxicology
• Computational biology
• Physiology

Selected publications

• Abstract 5031: Integrating real-world wearable data into breast cancer risk assessment: Evidence from the <i>All of Us</i> Research Program

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract Lifestyle and genetic factors are known contributors to breast cancer risk, yet their integration with clinical data into breast cancer risk assessment remains limited. Traditional, self-reported lifestyle measures are subject to recall bias, whereas wearable devices provide objective, continuous measurements of physical activity and sleep behaviors. Using data from the National Institutes of Health All of Us Research Program (n=633,540 participants), we conducted a retrospective matched case-control study to evaluate the association between objectively captured wearable data and breast cancer risk, and to establish a scalable analytical framework for causal and machine learning modeling. Females diagnosed with breast cancer at age ≥50 years with at least five valid weeks of Fitbit data (two or more days per week) within the five years preceding diagnosis (n=154) were each matched to up to 20 cancer-free controls by date of birth (±1 year) and availability of wearable data within the same time temporal window. Numerical variables were analyzed using Wilcoxon signed-rank tests, and categorical variables via chi-square analysis. Cases exhibited lower average daily steps (6766 ± 3040) compared to controls (7248 ± 3266; p=0.011), as well as fewer daily light active and very active minutes (179.8 ± 69.0 and 13.6 ± 13.7 vs. 190.2 ± 69.3 and 16.0 ± 16.9; p = 0.043 and p &amp;lt; 0.001, respectively). Sleep metrics were not significantly different between groups, while family history of breast cancer was more common among cases (p &amp;lt; 0.001). Building on these findings, we propose a multimodal integrative framework that merges wearable, survey, and electronic health record data, with future incorporation of genomic features and causal inference techniques (e.g., propensity score matching and causal forests) to refine individualized risk estimation. Explainable machine learning approaches, including ensemble and time-series models, will enable interpretable and dynamically updated risk predictions. This study demonstrates the feasibility of using real-world wearable data within the All of Us infrastructure and underscores the translational potential of multimodal, causal, and interpretable modeling for precision breast cancer screening and prevention at a population scale. Citation Format: Yoav Weber, Arshia Ilaty, Xuanxi Kuang, Emily Lan Nguyen, Abel Plaza-Florido, Shlomit Radom-Aizik, Argyrios Ziogas, Amir M. Rahmani, Hannah Lui Park. Integrating real-world wearable data into breast cancer risk assessment: Evidence from the All of Us Research Program [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5031.

  PublisherDOI

• Automated self-service cohort selection for large-scale population sciences and observational research: The California Teachers Study researcher platform

  PLoS ONE · 2025-05-12 · 1 citations

  articleOpen access

  OBJECTIVE: Cohort selection is ubiquitous and essential, but manual and ad hoc approaches are time-consuming, labor-intense, and difficult to scale. We sought to automate the task of cohort selection by building self-service tools that enable researchers to independently generate datasets for population sciences research. MATERIALS AND METHODS: The California Teachers Study (CTS) is a prospective observational study of 133,477 women who have been followed continuously since 1995. The CTS includes extensive survey-based and real-world data from cancer, hospitalization, and mortality linkages. We curated data from our data warehouse into a column-oriented database and developed a researcher-facing web application that guides researchers through the project lifecycle; captures researchers' inputs; and automatically generates custom and analysis-ready data, code, dictionaries, and documentation. RESULTS: Researchers can register, access data, and propose projects on the CTS Researcher Platform via our CTS website. The Platform supports cohort and cross-sectional study designs for cancer, mortality, and any other ICD-based phenotypes or endpoints. User-friendly prompts and menus capture analytic design, inclusion/exclusion criteria, endpoint definitions, censoring rules, and covariate selection. Our platform empowers researchers everywhere to query, choose, review, and automatically and quickly receive custom data, analytic scripts, and documentation for their research projects. Research teams can review, revise, and update their choices anytime. DISCUSSION: We replaced inefficient traditional cohort-selection processes with an integrated self-service approach that simplifies and improves cohort selection for all stakeholders. Compared with manual methods, our solution is faster and more scalable, user-friendly, and collaborative. Other studies could re-configure our individual database, project-tracking, website, and data-delivery components for their own specific needs, or they could utilize other widely available solutions (e.g., alternative database or project-tracking tools) to enable similarly automated cohort-selection in their own settings. Our comprehensive and flexible framework could be adopted to improve cohort selection in other population sciences and observational research settings.

  PublisherDOI

• Central and peripheral adiposity and premenopausal breast cancer risk: a pooled analysis of 440,179 women

  Breast Cancer Research · 2025-04-15 · 3 citations

  articleOpen access

  BACKGROUND: Among premenopausal women, higher body mass index (BMI) is associated with lower breast cancer risk, although the underlying mechanisms are unclear. Investigating adiposity distribution may help clarify impacts on breast cancer risk. This study was initiated to investigate associations of central and peripheral adiposity with premenopausal breast cancer risk overall and by other risk factors and breast cancer characteristics. METHODS: We used individual-level data from 14 prospective cohort studies to estimate hazard ratios (HRs) for premenopausal breast cancer using Cox proportional hazards regression. Analyses included 440,179 women followed for a median of 7.5 years (interquartile range: 4.0-11.3) between 1976 and 2017, with 6,779 incident premenopausal breast cancers. RESULTS: All central adiposity measures were inversely associated with breast cancer risk overall when not controlling for BMI (e.g. for waist circumference, HR per 10 cm increase: 0.92, 95% confidence interval (CI): 0.90-0.94) whereas in models adjusting for BMI, these measures were no longer associated with risk (e.g. for waist circumference: HR 0.99, 95% CI: 0.95-1.03). This finding was consistent across age categories, with some evidence that BMI-adjusted associations differed by breast cancer subtype. Inverse associations for in situ breast cancer were observed with waist-to-height and waist-to-hip ratios and a positive association was observed for oestrogen-receptor-positive breast cancer with hip circumference (HR per 10 cm increase: 1.08, 95% CI: 1.10-1.14). For luminal B, HER2-positive breast cancer, we observed an inverse association with hip circumference (HR per 10 cm: 0.84, 95% CI: 0.71-0.98), but positive associations with waist circumference (HR per 10 cm: 1.18, 95% CI: 1.03-1.36), waist-to-hip ratio (HR per 0.1 units: 1.29, 95% CI: 1.15-1.45) and waist-to height ratio (HR per 0.1 units: 1.46, 95% CI: 1.17-1.84). CONCLUSIONS: Our analyses did not support an association between central adiposity and overall premenopausal breast cancer risk after adjustment for BMI. However, our findings suggest associations might differ by breast cancer hormone receptor and intrinsic subtypes.

  PublisherOA PDFDOI

• Supplementary Table S4 from ALDH2 Deficiency and Alcohol Intake in the United States: Opportunity for Precision Cancer Prevention

  2025-05-02

  supplementary-materialsOpen accessSenior author

  &lt;p&gt;Supplementary Table S4 presents results from logistic regression analyses examining factors associated with alcohol consumption and binge drinking. The analyses were conducted separately for the overall cohort and for ALDH2*2 carriers only.&lt;/p&gt;

  PublisherOA PDFDOI

• Hormone therapy use and young-onset breast cancer: a pooled analysis of prospective cohorts included in the Premenopausal Breast Cancer Collaborative Group

  The Lancet Oncology · 2025-07-01 · 9 citations

  article
  PublisherDOI

• Abstract P3-03-03: Disparities in Quality of Life Among Breast Cancer Survivors in the All of Us Research Program

  Clinical Cancer Research · 2025-06-13

  articleSenior author

  Abstract Background: Breast cancer is the most common cancer among women. Advancements in breast cancer treatment and early diagnosis have resulted in higher survival rates necessitating the importance of studying quality of life (QOL) among breast cancer survivors. QOL is an important endpoint in clinical trials as it provides insights into the overall well being and long-term outcomes of patients. Understanding QOL is also crucial for guiding treatment decisions, supporting survivorship care, and shaping healthcare policy. Previous studies have shown that racial/ethnic disparities in QOL exist, and factors affecting QOL have been investigated. However, inconsistencies remain regarding specific determinants, and a large-scale study examining disparities in QOL among breast cancer survivors in the U.S. has not been done. Methods: We analyzed data from 2,022 female breast cancer survivors in the National Institutes of Health's All of Us Research Program database. QOL (scored from 1 to 5) was measured using survey response data in which participants answered the question: “In general, would you say your quality of life is – excellent (5), very good (4), good (3), fair (2), or poor (1).” Univariable and multivariable linear regression analyses were performed to identify demographic, socioeconomic and psychosocial factors associated with QOL. The multivariable analysis consisted of using Bonferroni correction and stepwise regression to adjust the p-values for multiple tests and to select the most statistically relevant variables contributing to QOL, respectively. Results: The cohort was predominantly non-Hispanic White (84%), with the remaining participants being non-Hispanic Black (5.5%), Hispanic (3.1%), Other/Mixed (2.6%), and non-Hispanic Asian (1.6%). The average age was 70 years old. In the multivariable analyses, non-Hispanic Black (β= -0.33, 95%CI: [−0.49, −0.18], p &amp;lt; 0.005) and Hispanic (β= -0.38, 95%CI: [−0.58, −0.18], p &amp;lt; 0.005) survivors had lower QOL compared to non-Hispanic white survivors. For each additional year of age, the QOL score slightly increased by 0.01 units (95%CI: [0.009, 0.018], p &amp;lt; 0.001). Lower education (high school or lower) (β= -0.28, 95%CI: [-0.42, -0.14], p &amp;lt; 0.005) and lower household income levels (annual household income less than $25,000K) (β= -0.66, 95%CI: [-0.84, -0.48], p &amp;lt; 0.001) were also significantly associated with lower QOL. Interestingly, lacking confidence in filling out medical forms (β= -0.53, 95%CI: [-0.79, -0.28], p &amp;lt; 0.005) and feeling that medical providers were not listening (β= -0.22, 95%CI: [-0.29, -0.15 AZ], p &amp;lt; 0.001) were associated with lower QOL. Conversely, having assistance with daily tasks all or most of the time (β= 0.32, 95%CI: [0.19,0.45], p &amp;lt; 0.001) was linked to a higher quality of life. Conclusion: In the national All of Us cohort, quality of life was associated with age, race and ethnicity, age, other socioeconomic factors, and psychosocial factors. Enhancing the availability of daily assistance and improving patient-provider communication can help mitigate some of these disparities. Our findings suggest that recognizing populations at risk and connecting them to resources with social work, support groups, and survivorship clinics will impact survivors’ quality of life. Citation Format: Gagandeep Kaur, Jiayuan Wang, An D Truong, Hester Nguyen, Leah Puglisi, Carrie Costantini, Ritesh Parajuli, Hannah Lui Park. Disparities in Quality of Life Among Breast Cancer Survivors in the All of Us Research Program [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P3-03-03.

  PublisherDOI

• Supplementary Table S4 from ALDH2 Deficiency and Alcohol Intake in the United States: Opportunity for Precision Cancer Prevention

  2025-05-02

  supplementary-materialsOpen accessSenior author

  &lt;p&gt;Supplementary Table S4 presents results from logistic regression analyses examining factors associated with alcohol consumption and binge drinking. The analyses were conducted separately for the overall cohort and for ALDH2*2 carriers only.&lt;/p&gt;

  PublisherOA PDFDOI

• Data from ALDH2 Deficiency and Alcohol Intake in the United States: Opportunity for Precision Cancer Prevention

  2025-05-02

  preprintOpen accessSenior author

  &lt;div&gt;AbstractBackground:&lt;p&gt;Alcoholic beverages and the main metabolite of alcohol, acetaldehyde, are known carcinogens. A genetic variant in &lt;i&gt;aldehyde dehydrogenase 2&lt;/i&gt; (&lt;i&gt;ALDH2&lt;/i&gt;, G&gt;A, rs671) leads to decreased efficiency in metabolizing acetaldehyde and is associated with an increased cancer risk. As alcohol consumption is a modifiable risk factor for various cancers, the identification of ALDH2 deficiency presents an opportunity for precision cancer prevention.&lt;/p&gt;Methods:&lt;p&gt;Our primary objectives were to examine the prevalence of ALDH2 deficiency and alcohol consumption behavior among affected individuals within a large, diverse US national cohort. The prevalence of ALDH2 deficiency was determined by examining the rs671 genotype among 311,290 participants within the &lt;i&gt;All of Us&lt;/i&gt; Research Program. Relationships among self-reported alcohol consumption, sociodemographic factors, and the rs671 genotype were analyzed.&lt;/p&gt;Results:&lt;p&gt;ALDH2 deficiency was most prevalent among individuals who identified as Asian, among whom 23.5% had at least one deficient &lt;i&gt;ALDH2&lt;/i&gt; allele compared with &lt;2.5% in all other racial/ethnic groups. Among those with one and two deficient &lt;i&gt;ALDH2&lt;/i&gt; alleles, 61.2% and 24.4% reported drinking in the past year, respectively, and of these, 30.3% and 16.0% reported binge drinking. Multivariable analysis showed that &lt;i&gt;ALDH2&lt;/i&gt; genotype&lt;i&gt;,&lt;/i&gt; sex, age, race, education, income, employment, marital status, and country of birth were associated with alcohol consumption behavior.&lt;/p&gt;Conclusions:&lt;p&gt;Most individuals with ALDH2 deficiency reported drinking alcohol in the past year, and consumption was associated with various sociodemographic variables, particularly sex, age, and country of birth.&lt;/p&gt;Impact:&lt;p&gt;Our findings suggest a significant opportunity for precision cancer prevention targeting the unique prevalence of ALDH2 deficiency among Asian Americans.&lt;/p&gt;&lt;/div&gt;

  PublisherDOI

• Supplementary Table S3 from ALDH2 Deficiency and Alcohol Intake in the United States: Opportunity for Precision Cancer Prevention

  2025-05-02

  supplementary-materialsOpen accessSenior author

  &lt;p&gt;Supplementary Table S3 shows the distribution of ALDH2 genotypes across racial groups using uncollapsed categories.&lt;/p&gt;

  PublisherOA PDFDOI

• Supplementary Table S1 from ALDH2 Deficiency and Alcohol Intake in the United States: Opportunity for Precision Cancer Prevention

  2025-05-02

  supplementary-materialsOpen accessSenior author

  &lt;p&gt;Supplementary Table S1 outlines how variables were recategorized from the original survey responses. It shows the final categories used in our analysis (left column) and maps them to the corresponding response options from the All of Us Research Program survey questions (right column).&lt;/p&gt;

  PublisherOA PDFDOI

Frequent coauthors

• David Sidransky

  Johns Hopkins University

  65 shared

• Cathryn H. Bock

  Wayne State University

  64 shared

• Allison Jay

  Ascension

  64 shared

• Ilir Agalliu

  Montefiore Medical Center

  64 shared

• Nancie Petrucelli

  The Barbara Ann Karmanos Cancer Institute

  64 shared

• Annette Peters

  Deutsches Diabetes-Zentrum e.V.

  64 shared

• JoAnn E. Manson

  Brigham and Women's Hospital

  64 shared

• Fridtjof Thomas

  University of Tennessee Health Science Center

  64 shared

Labs

• Park LabPI

Education

• Ph.D., Biological Sciences

  Stanford University

• M.S., Cell and Neurobiology

  University of Southern California Keck School of Medicine

• B.A., Molecular and Cell Biology

  University of California, Berkeley